import os
import csv
from tqdm import tqdm
import time
import math
import random
import numpy as np
random.seed(2024)
# from lightgbm import LGBMClassifier, Booster

from sklearn.metrics import roc_auc_score
# from sklearn.neural_network import MLPClassifier
from sklearn.tree import DecisionTreeClassifier
# from sklearn.svm import SVC

project_dir = os.path.dirname(os.path.abspath(__file__))
project_dir = project_dir.replace('scripts','')
import sys
sys.path.append(project_dir)

filename = os.path.join(project_dir, 'data/train_prob.csv')
train_features,train_labels = [],[]
test_features,test_labels = [],[]
with open(filename, 'r', encoding='utf-8') as f:
    lines = csv.reader(f)
    next(lines)
    for line in lines:
        